A family of kurtosis orderings for multivariate distributions

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

In this paper, a family of kurtosis orderings for multivariate distributions is proposed and studied. Each ordering characterizes in an affine invariant sense the movement of probability mass from the "shoulders" of a distribution to either the center or the tails or both. All even moments of the Mahalanobis distance of a random vector from its mean (if exists) preserve a subfamily of the orderings. For elliptically symmetric distributions, each ordering determines the distributions up to affine equivalence. As applications, the orderings are used to study elliptically symmetric distributions. Ordering results are established for three important families of elliptically symmetric distributions: Kotz type distributions, Pearson Type VII distributions, and Pearson Type II distributions.

Original languageEnglish (US)
Pages (from-to)509-517
Number of pages9
JournalJournal of Multivariate Analysis
Volume100
Issue number3
DOIs
StatePublished - Mar 2009

Fingerprint

Kurtosis
Multivariate Distribution
Elliptically Symmetric Distributions
Affine Invariant
Mahalanobis Distance
Random Vector
Tail
Equivalence
Family
Multivariate distribution
Moment

Keywords

  • 62G05
  • 62H05
  • Elliptically symmetric distributions
  • Kurtosis
  • Ordering
  • Peakedness
  • primary
  • secondary
  • Tailweight

ASJC Scopus subject areas

  • Statistics, Probability and Uncertainty
  • Numerical Analysis
  • Statistics and Probability

Cite this

A family of kurtosis orderings for multivariate distributions. / Wang, Jin.

In: Journal of Multivariate Analysis, Vol. 100, No. 3, 03.2009, p. 509-517.

Research output: Contribution to journalArticle

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